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Mapping Cumulative Environmental Risks: Examples from the EU NoMiracle Project

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Abstract

We present examples of cumulative chemical risk mapping methods developed within the NoMiracle project. The different examples illustrate the application of the concentration addition (CA) approach to pesticides at different scale, the integration in space of cumulative risks to individual organisms under the CA assumption, and two techniques to (1) integrate risks using data-driven, parametric statistical methods, and (2) cluster together areas with similar occurrence of different risk factors, respectively. The examples are used to discuss some general issues, particularly on the conventional nature of cumulative risk maps, and may provide some suggestions for the practice of cumulative risk mapping.

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References

  1. Aller, L., Bennet, T., et al. (1987). DRASTIC, a standardized system for evaluating groundwater pollution potential using hydrogeologic setting. U.S. Environmental Protection Agency, EPA, Report 600/2-87-035; 1-455.

  2. Bartels, C. J., & Van Beurden, A. U. C. J. (1998). Using geographic and cartographic principles for environmental assessment and risk mapping. Journal of Hazardous Materials, 61, 115–124.

    Article  CAS  Google Scholar 

  3. Best, N., Richardson, S., & Elliott, P. (2003) Spatial epidemiology. Short Course, September 8–9.

  4. BImSchV, 22 (2007) Verordnung zur Durchführung des Bundes-Immissionschutzgesetzes (Verordnung über Immissionswerte für Schadstoffe in der Luft). Bundesminister für Umwelt, Naturschutz und Reaktorsicherheit.

  5. Bliss, C. I. (1939). The toxicity of poisons applied jointly. The Annals of Applied Biology, 26, 585–615.

    Article  CAS  Google Scholar 

  6. Boedeker, W., Drescher, K., Altenburger, R., Faust, M., & Grimme, L. H. (1993). Combined effects of toxicants: the need and soundness of assessment approaches in ecotoxicology. Science of the Total Environment, 134(2), 931–938.

    Article  Google Scholar 

  7. Bonzini, S., Verro, R., Otto, S., Lazzaro, L., Finizio, A., Zanin, G., et al. (2006). Experimental validation of a GIS-based procedure for predicting pesticide exposure in surface water. Environmental Science & Technology, 40, 7561–7569.

    Article  CAS  Google Scholar 

  8. Chung, C. F., & Fabbri, A. G. (1993). The representation of geoscience information for data integration. Nonrenewable Resources, 2(2), 122–139.

    Article  Google Scholar 

  9. Chung, C. F., & Fabbri, A. G. (1999). Probabilistic prediction models for landslide hazard mapping. Photogrammetric Engineering and Remote Sensing, 65(12), 1389–1399.

    Google Scholar 

  10. De Lange, H. J., Sala S., Vighi M., & Faber J. H. (2010) Ecological vulnerability in risk assessment—A review and perspectives. Science of the Total Environment (in press)

  11. de Zwart, D. (2005). Ecological effects of pesticide use in the Netherlands: modeled and observed effects in the field ditch. Integrated Environmental Assessment and Management, 1(2), 123–134.

    Article  Google Scholar 

  12. Drescher, K., & Boedeker, W. (1995). Assessment of the combined effects of substances: the relationship between concentration addition and independent action. Biometrics, 51, 716–730.

    Article  Google Scholar 

  13. Elliott, P., & Wartenberg, D. (2004). Spatial epidemiology: current approaches and future challenges. Environmental Health Perspectives, 112, 998–1006.

    Article  Google Scholar 

  14. Faust, M., Altenburger, R., Backhaus, T., Blanck, H., Bödeker, W., Gramatica, P., et al. (2003). Joint algal toxicity of 16 dissimilarly acting chemicals is predictable by the concept of independent action. Aquatic Toxicology, 63, 43–63.

    Article  CAS  Google Scholar 

  15. Finizio, A., Calliera, M., & Vighi, M. (2001). Rating systems for pesticide risk classification on different ecosystems. Ecotoxicology and Environmental Safety, 49, 262–274.

    Article  CAS  Google Scholar 

  16. Finizio, A., Villa, S., & Vighi, M. (2005). Predicting pesticide mixtures load in surface waters from a given crop. Agriculture, Ecosystems & Environment, 111, 111–118.

    Article  CAS  Google Scholar 

  17. Greco, W., Unkelbach, H. D., Pöch, G., Suhnel, J., Kundi, M., & Bodeker, W. (1992). Consensus on concepts and terminology for combined-action assessment: the Saariselkä agreement. Archives of Complex Environmental Studies, 4(3), 65–72.

    Google Scholar 

  18. Hansen, A. B., & Palmgren, F. (1996). VOC air pollutants in Copenhagen. The Science of the Total Environment, 190, 451–457.

    Article  Google Scholar 

  19. Hollands, J. G., & Spence, I. (1998). Judging proportion with graphs: the summation model. Applied Cognitive Psychology, 12, 173–190.

    Article  Google Scholar 

  20. Husdal, J. (2001) Can it be that dangerous? Issues in visualization of risk and vulnerability. http://husdal.typepad.com/blog/2001/10/can-it-really-b.html.

  21. Ippolito, A., Sala, S., Faber, J. H., & Vighi, M. (2010) Application of vulnerability analysis; a case study of river basin. Science of the Total Environment (in press).

  22. Jarosinska, D. (2009). Protecting human health and ecosystems—connecting novel research, practice and policy on multiple stressors Proc. NoMiracle/PHIME Conference “Multiple Stressors—Novel Methods for Integrated Risk Assessment” Aarhus, Denmark, 28th–30th September. http://nomiracle.jrc.ec.europa.eu/Documents/Conference_28-30_September_2009/Proceedings.pdf.

  23. Jo, W. K., Lee, J. W., & Shin, D. C. (2004). Exposure to volatile organic compounds in residences adjacent to dyeing industrial complex. International Archives of Occupational and Environmental Health, 77(2), 113–120.

    Article  CAS  Google Scholar 

  24. Junghans, M., Backhaus, T., Faust, M., Scholze, M., & Grimme, L. H. (2006). Application and validation of approaches for the predictive hazard assessment of realistic pesticide mixtures. Aquatic Toxicology, 76, 93–110.

    Article  CAS  Google Scholar 

  25. Kangas, J. A., Kohonen, T. K., & Laaksonen, J. T. (1990). Variants of self-organizing maps. IEEE Transactions on Neural Networks, 1, 93–99.

    Article  CAS  Google Scholar 

  26. Kaski, S. (1997). Data exploration using Self-Organizing Maps. Dissertation for the degree of Doctor of Technology, Helsinki University of Technology, Espoo.

  27. Kohonen, T. (1990). The self-organizing map. Proc IEEE, 78, 1464–1480.

    Article  Google Scholar 

  28. Lahr, J., & Kooistra, L. (2009) Environmental risk mapping: state of the art and communication aspects. Science of the Total Environment (in press).

  29. Lahr, J., & Kooistra, L. (2010). Environmental risk mapping of pollutants: state of the art and communication aspects. Science of the Total Environment. doi:10.1026/j.scitotenv.2009.10.045.

    Google Scholar 

  30. Loos, M., Ragas, A. M. J., Plasmeijer, M. J., & Hendriks, A. J. (2010) A receptor-oriented ecological exposure model for terrestrial vertebrates in an object-oriented programming platform. Science of the Total Environment (in press).

  31. Moen, J. E. T., & Ale, B. J. M. (1998). Risk maps and communication. Journal of Hazardous Materials, 61, 271–278.

    Article  CAS  Google Scholar 

  32. Nelson, P. (2000). Australia's national plan to combat pollution of the sea by oil and other noxious and hazardous substances—overview and current issues. Spill Science & Technology Bulletin, 6, 3–11.

    Article  Google Scholar 

  33. Pekey, H., & Arslanbas, D. (2008). The relationship between indoor, outdoor and personal VOC concentrations in homes, offices and schools in the metropolitan region of Kocaeli, Turkey. Water, Air, and Soil Pollution, 191(1–4), 113–129.

    Article  CAS  Google Scholar 

  34. Piscopo, G. (2001). Groundwater vulnerability map explanatory notes, Castlereagh Catchment. NSW Department of Land and Water Conservation, Australia.

  35. Pistocchi, A., & Bidoglio, G. (2009) Is it presently possible to assess the spatial distribution of agricultural pesticides for continental Europe? A screening study based on available data.

  36. Pistocchi, A., Luzi, L., & Napolitano, P. (2002). The use of predictive modeling techniques for optimal exploitation of spatial databases: a case study in landslide hazard mapping with expert-system-like methods. Environmental Geology, 41(7), 765–775.

    Article  Google Scholar 

  37. Pistocchi, A., Vizcaino, P., & Hauck, M. (2010) A GIS model-based screening of potential contamination of soil and water by pyrethroids in Europe. Journal of Environmental Management. ISSN 0301-4797. doi:10.1016/j.jenvman.2009.05.020.

  38. Pistocchi, A., Vizcaino, P., & Sarigiannis, D. Spatially explicit multimedia fate models for pollutants in Europe: state of the art and perspectives. Science of the Total Environment. doi:10.1016/j.scitotenv.2009.10.046

  39. Plackett, R. L., & Hewlett, P. S. (1952). Quantal responses to mixtures of poisons. Journal of the Royal Statistical Society. Series B, 14, 141–163.

    Google Scholar 

  40. Price, P. S., Chaisson, C. F., Koontz, M., Wilkes, C., Ryan, B., Macintosh, D., et al. (2003). Construction of a comprehensive chemical exposure framework using person-oriented modeling. Annandale: The LifeLine Group. 129 pp.

    Google Scholar 

  41. Sala, S., & Vighi, M. (2007). GIS-based procedure for site-specific risk assessment of pesticides for aquatic ecosystems. Ecotoxicology and Environmental Safety, 69(1), 1–12.

    Article  Google Scholar 

  42. Sattler, B., Lippy, B., & Jordan T. (1997) Hazard communication: a review of the science underpinning the art of communication for health and safety. US Department of Labor, Washington, DC. http://www.osha.gov/SLTC/hazardcommunications/hc2inf2.html. Accessed May 2009

  43. Schipper, A. M., Loos, M., Ragas, A. M. J., Lopes, J. P. C., Nolte, B., Wijnhoven, S., et al. (2008). Modeling the influence of environmental heterogeneity on heavy metal exposure concentrations for terrestrial vertebrates in river floodplains. Environmental Toxicology and Chemistry, 27, 919–932.

    Article  CAS  Google Scholar 

  44. Schlink, U., Rehwagen, M., Damm, M., Richter, M., Borte, M., & Herbarth, O. (2004). Seasonal cycle of indoor-VOCs: comparison of apartments and cities. Atmospheric Environment, 38(8), 1181–1190.

    Article  CAS  Google Scholar 

  45. Schneider, P., Gebefugi, I., Richter, K., Wolke, G., Schnelle, J., Wichmann, H. E., et al. (2001). Indoor and outdoor BTX levels in German cities. The Science of the Total Environment, 267(1–3), 41–51.

    Article  CAS  Google Scholar 

  46. Srivastava, A. (2005). Variability in VOC concentrations in an urban area of Delhi. Environmental Monitoring and Assessment, 107(1–3), 363–373.

    Article  CAS  Google Scholar 

  47. Tait, N. G., Lerner, D. N., Smith, J. W. N., & Leharne, S. A. (2004). Prioritisation of abstraction boreholes at risk from chlorinated solvent contamination on the UK Permo-Triassic sandstone aquifer using a GIS. The Science of the Total Environment, 319, 77–98.

    Article  CAS  Google Scholar 

  48. Thomas, A., Best, N., Lunn, D., Arnold, R., & Spiegelhalter, D. (2004). GeoBUGS user manual, version 1.2. Cambridge: Medical Research Council Biostatistics Unit; 2004. http://www.mrcbsu.cam.ac.uk/bugs/winbugs/geobugs.shtml.

  49. Tortell, P. (1992). Coastal zone sensitivity mapping and its role in marine environmental management. Marine Pollution Bulletin, 25, 88–93.

    Article  Google Scholar 

  50. Van der Linden, A. M. A., Luttik, R., Deneer, J. W., & Smidt, R. A. (2004). Dutch environmental indicator for plant protection products. Description of input data and calculation methods. Report no. 716601009/2004, RIVM/Alterra, Bilthoven/Wageningen, The Netherlands.

  51. Van der Linden A. M. A., van Beelen, P., van den Berg, G. A., de Boer, M., van der Gaag, D. J., Groenwold, J. G., et al. (2006) Evaluation sustainable crop protection. Report nr. RIVM607016001, RIVM, Bilthoven, The Netherlands.

  52. Van der Linden, A. M. A., Luttik, R., Groenwold, J. G., Kruijne en, R., & Merkelbach, R. C. M. (2008). Dutch Environmental Indicator for plant protection products, version 2. Input, calculation and aggregation procedures, Report nr. 607600002/2008, RIVM, Bilthoven, The Netherlands.

  53. Van Leeuwen, C. J., & Hermens, J. L. M. (1995). Risk assessment of chemicals: An introduction. Dordrecht: Kluwer. 374 pp.

    Google Scholar 

  54. U.S. EPA (2006). Considerations for Developing Alternative Health Risk Assessment Approaches for Addressing Multiple Chemicals, Exposures and Effect (External Review Draft). U.S. Environmental Protection Agency, Washington, D.C., EPA/600/R-06/014A, 2006.

  55. Verro, R., Finizio, A., Otto, S., & Vighi, M. (2009). Predicting pesticide environmental risk in intensive agricultural areas. II: Screening level risk assessment of complex mixtures in surface waters. Environmental Science & Technology, 43, 530–53.

    Article  CAS  Google Scholar 

  56. Verro, R., Finizio, A., Otto, S., & Vighi, M. (2009). Predicting pesticide environmental risk in intensive agricultural areas. I: Screening level risk assessment of individual chemicals in surface waters. Environmental Science & Technology, 43, 522–529.

    Article  CAS  Google Scholar 

  57. Vesanto, J. (1999). SOM-based data visualization methods. Intelligent Data Analysis, 3, 11–126.

    Article  Google Scholar 

  58. Vesanto, J., & Alhoniemi, E. (2000). Clustering of the self-organizing map. IEEE Transactions on Neural Networks, 11, 586–600.

    Article  CAS  Google Scholar 

  59. Wogalter, M. S., Conzola, V. C., & Smith-Jackson, T. L. (2002). Research-based guidelines for warning design and evaluation. Applied Ergonomics, 33, 219–230.

    Article  Google Scholar 

  60. Wood, M., & Jelínek, R. (2007) Risk mapping in the new member states. A summary of general practices for mapping hazards, vulnerability and risk. Report no. EUR 22899 EN, Institute for the Protection and Security of the Citizen, Joint Research Centre, European Commission, Ispra, Italy, 26 pp.

  61. Woodbury, P. B. (2003). DOs and DON’Ts of spatially explicit ecological risk assessment. Environmental Toxicology and Chemistry, 22, 977–982.

    Article  CAS  Google Scholar 

  62. Worrall, F., & Besien, T. (2005). The vulnerability of groundwater to pesticide contamination estimated directly from observations of presence or absence in wells. Journal of Hydrology, 303, 92–107.

    Article  CAS  Google Scholar 

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Acknowledgments

This paper contains considerations jointly developed by different partners of the NoMiracle project consortium. The individual case studies presented here are provided by single partners, to which the reader may refer for further details and for all scientific aspects not related to the specific topic of risk mapping: A. Pistocchi and P. Vizcaino for the European mapping of pesticides, S. Sala and M. Vighi for the case study on pesticides in Lombardy, J. Groenwold and J. Lahr for the one on pesticides in the Netherlands, M. Loos and A. Ragas for the case study on risks to individual organisms, U. Schlink and K. Strebel for the case of benzene in Leipzig, and M. Mujica and R. Rallo for the case on aquifer vulnerability mapping in Catalonia. J. Lahr coordinated the mapping exercises within the frame of NoMiracle Project work package 4.4, while A. Pistocchi coordinated the writing of the paper. The research was partly funded by the European Commission FP6 contract no. 003956 (NoMiracle IP: http://nomiracle.jrc.ec.europa.eu). Funding of Alterra, Wageningen UR, was also obtained from the Strategic research program “Sustainable spatial development of ecosystems, landscapes, seas and regions” financed by the Dutch Ministry of Agriculture, Nature Conservation and Food Quality (LNV).

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Correspondence to Alberto Pistocchi.

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Supporting information

A document of supporting information is available along with the paper, containing additional material for the illustration of the case studies presented here.

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Figure S1

Sample map of mass equivalent (criterion: acute toxicity to earthworms) (DOC 1108 kb)

Figure S2

Average potential ecological effects per grid cell of three insecticides calculated by the NMI for the year 1998 (DOC 26 kb)

Figure S3

Potential effects of chlorpyrifos on water organisms in 1998 calculated by the NMI (DOC 435 kb)

Figure S4

Potential effects of chlorpyrifos leaching to groundwater in 1998 calculated by the NMI (DOC 228 kb)

Figure S5

Accumulated potential effects of three insecticides (chlorpyrifos, imidacloprid, and diazinon) on water organisms in 1998 calculated by the NMI (DOC 436 kb)

Figure S6

Average potential effects of diazinon on water organisms during 1998 calculated by the NMI (DOC 26 kb)

Table S1

Criteria for risk indicator mapping at European scale: summary of HAIR indicators and maps to be used (E = emission; D = drift; M = mass in soil; L = loads to water bodies; C w = concentration in soil water phase) (DOC 30 kb)

Table S2

Available toxicological parameters for the chemicals considered in this study (DOC 28 kb)

Table S3

Substance classes used in the present study (DOC 53 kb)

Table S4

Properties of three pesticides used for demonstration (DOC 32 kb)

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Pistocchi, A., Groenwold, J., Lahr, J. et al. Mapping Cumulative Environmental Risks: Examples from the EU NoMiracle Project. Environ Model Assess 16, 119–133 (2011). https://doi.org/10.1007/s10666-010-9230-6

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